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摘要:分析了基于遗传算法的无功优化在实际系统应用中存在的问题,在传统遗传算法的基础上,对适应度函数和群体多样性的保持进行了改进,并将设备动作优先级和历史负荷经验数据引入遗传算法,根据福建电网的实际情况完成了遗传算法在无功优化中的实用化改进。实际应用表明,改进后的算法使得控制设备动作合理,动作次数少,能有效地提高电网的电压合格率并降低网损。
Abstract: This paper analyzes the problems existing in practical application of reactive power optimization based on genetic algorithm. On the basis of traditional genetic algorithm, the fitness function and the diversity of population are improved. The priority of equipment action and history Based on the actual situation of Fujian Power Grid, genetic algorithm is introduced into the experience data of load, and the practical improvement of genetic algorithm in reactive power optimization is completed. The practical application shows that the improved algorithm makes the control equipment operate rationally with less operation times, which can effectively improve the grid voltage compliance rate and reduce the network loss.